TWM606890U - Transaction abnormality evaluation system - Google Patents

Abstract

This creation is a transaction abnormality evaluation system, including a data input device that can provide input transaction information to a connected abnormality evaluation and analysis device. The abnormality evaluation and analysis device contains risk evaluation conditions, so that the abnormality evaluation and analysis device can make judgments based on the risk evaluation conditions. The transaction information provided by the data input device to generate a transaction risk index. A display device is connected to the abnormality evaluation and analysis device to receive and display the transaction risk index. This creation uses artificial intelligence learning to analyze whether the transaction is fraudulent or money laundering, so as to monitor the transaction situation in real time, improve transaction security, and save work time to improve the effectiveness of anti-fraud and anti-money laundering.

Description

Transaction anomaly evaluation system

This creation is related to a data processing system, especially a transaction abnormality evaluation system that can predict transaction abnormalities.

In the society, financial fraud and money laundering and other bad transaction behaviors emerge one after another. Especially when a user is scammed by a scam group, the user is likely to lose the ability to judge because of the current emotions, and misbelieve the forged information spread by the scam group. To prevent this kind of bad transaction behavior, the user can only rely on the user to visit the financial When the institution withdraws or transfers money, the staff of the financial institution actively discovers that the user has been scammed and prevents the user from sending money. However, there are many businesses that financial institution employees have to deal with, and it is very likely that the employees will not be able to immediately detect that the user has suffered fraud, so that they cannot prevent the user from sending money, resulting in irreparable consequences.

In addition, with the gradual development of Internet technology, online banking services can handle more and more businesses. Many users may choose to use online banking to transfer money when they are subjected to fraud or money laundering. At this time, the process of financial transactions will not go through financial institution staff. Without the check of financial institution staff, financial transactions of fraud or money laundering cannot be prevented immediately, making financial transaction fraud or money laundering more difficult to prevent.

In view of this, this author proposes a transaction anomaly evaluation system that can automatically learn and establish specifications to analyze and predict current transaction operations in order to automatically predict fraud or money laundering. To effectively overcome the above-mentioned problems.

The main purpose of this creation is to provide a transaction abnormality evaluation system, which can automatically analyze the possible fraud or money laundering behavior during transactions, so as to monitor the transaction situation in real time and improve transaction security.

Another purpose of this creation is to provide a transaction abnormality evaluation system, which can introduce artificial intelligence to analyze transactions that may cause fraud or money laundering, which can reduce manpower to investigate bad transactions, save work time and improve anti-fraud and anti-money laundering performance.

Another purpose of this creation is to provide a transaction abnormality evaluation system, which can still automatically determine whether the transaction is fraudulent or money laundering when the automatic machine equipment conducts a transaction, so as to improve transaction security.

To achieve the above-mentioned purpose, this creation provides a transaction abnormality evaluation system, which includes a data input device to provide input transaction information. An abnormality evaluation and analysis device is connected to the data input device. The abnormality evaluation and analysis device contains risk evaluation conditions. The abnormality evaluation and analysis device receives transaction information and judges the transaction information according to the risk evaluation conditions to generate a transaction risk index. A display device is connected to the abnormality evaluation and analysis device to receive and display the transaction risk index.

In this embodiment, the transaction information includes beneficiary region information, beneficiary industry information, user business information, standard condition information, and user transfer channel information.

In this embodiment, the abnormality assessment and analysis device further includes a regional risk assessment unit and a regional risk weight table, which includes plural risk region information and a regional weight value corresponding to each risk region information. The regional risk assessment unit receives the receiving region Information, so that the receiving area information corresponds to the area weight value according to the area risk weight table. An industry risk assessment unit contains an industry risk weight table, which includes multiple risk industry information and industry weight values corresponding to each risk industry information. The industry risk assessment unit receives the payee’s industry information so that the payee’s industry information is based on the industry risk The weight table generates corresponding industry weight values. A business risk assessment unit contains a business risk weight table, which includes plural risk business information and a business weight value corresponding to each risk business information. The business risk assessment unit receives user business information and makes the user business information correspondingly generated according to the business risk weight table Business weight value. A standard risk assessment unit contains a standard risk weight table, which includes plural risk standard information and a standard weight value corresponding to each risk standard information. The standard risk assessment unit receives the standard condition information so that the standard condition information is generated according to the standard risk weight table. Standard weight value. A transaction channel risk assessment unit contains a transaction channel risk weight table, which includes plural risk transaction channel information and a transaction channel weight value corresponding to each risk transaction channel information. The transaction channel risk assessment unit receives user transfer channel information and enables the user to transfer The channel information generates the transaction channel weight value corresponding to the transaction channel risk weight table.

In this embodiment, the risk assessment conditions include a regional risk weight table, an industry risk weight table, a business risk weight table, a standardized risk weight table, and a transaction pipeline risk weight table.

In this embodiment, the abnormality assessment and analysis device further includes a weight integration unit, which is connected to the regional risk assessment unit, the business risk assessment unit, the normative risk assessment unit, and the transaction pipeline risk assessment unit to receive and analyze the regions generated by the abnormality assessment analysis device. The sum of weight value, industry weight value, business weight value, norm weight value and transaction channel weight value to generate a transaction risk index.

In this embodiment, the data input device can be a keyboard or a signal port.

In this embodiment, the display device may be a screen.

In this embodiment, the abnormality analysis and evaluation device is a computer.

In order to have a better understanding and understanding of the structural features of this creation and the effects achieved, I would like to provide a better embodiment diagram and detailed descriptions. The description is as follows.

The transaction anomaly evaluation system of this creation can import artificial intelligence analysis to automatically analyze whether the user’s transaction has been fraudulent or money laundering. Through the technology of this creation, even if the user uses automatic machinery and equipment to trade, it can still be monitored in real time. The transaction situation can improve transaction security, and at the same time, it can reduce the time for manpower to investigate bad transactions, so as to greatly save manpower time and improve the effectiveness of anti-fraud and anti-money laundering.

In order to explain how this creation achieves the above-mentioned effects, the following will further explain the structure of the creation transaction abnormality evaluation system and the operation of internal devices. Referring to the first figure, the transaction abnormality evaluation system 1 includes a data input device 10, an abnormality evaluation and analysis device 12, and a display device 14. The abnormality evaluation and analysis device 12 is signally connected to the data input device 10 and the display device 14 respectively. In this embodiment, the data input device 10 can be a keyboard input device, or can also be connected to a signal port of an external device to provide an external device to input transaction information to the transaction abnormality evaluation system 1, wherein the transaction information includes Regional information, payee industry information, user business information, standard condition information, and user transfer channel information. The abnormality evaluation and analysis device 12 may be a computer for analyzing the transaction information provided by the data input device 10 and determine the transaction information according to the risk evaluation conditions set in the abnormality evaluation and analysis device 12 to generate a transaction risk index. 14 of the display device can be a screen to display the trading risk index.

The abnormality assessment analysis device 12 further includes a regional risk assessment unit 120, an industry risk assessment unit 122, a business risk assessment unit 124, a normative risk assessment unit 126, a transaction pipeline risk assessment unit 128, and a weight integration unit 129. The weight integration unit 129 signally connects the regional risk assessment unit 120, the industry risk assessment unit 122, the business risk assessment unit 124, the normative risk assessment unit 126, and the transaction pipeline risk assessment unit 128. The weight integration unit 129 can integrate the data of the above risk assessment units. To generate a trading risk index. Among them, the risk assessment conditions used in the abnormal assessment analysis device 12 to determine the transaction information include the regional risk weight table, the industry risk weight table, the business risk weight table, the regulated risk weight table, and the transaction pipeline risk weight table. The above risk weight tables provide They are respectively stored in the regional risk assessment unit 120, the industry risk assessment unit 122, the business risk assessment unit 124, the normative risk assessment unit 126, and the transaction pipeline risk assessment unit 128 as parameters for judging the transaction risk index.

When the transaction information is input to the abnormal evaluation and analysis device 12, the beneficiary region information, beneficiary industry information, user business information, regulatory condition information, and user transfer channel information in the transaction information will sequentially enter the regional risk assessment unit 120, industry risk The evaluation unit 122, the business risk evaluation unit 124, the standard risk evaluation unit 126, and the transaction pipeline risk evaluation unit 128 respectively correspond to the geographical risk weight table, industry risk weight table, business risk weight table, and standard risk weight table in the risk evaluation unit. The weight value is generated by comparison with the risk weight table of the transaction channel, and is input to the weight integration unit 129, so that the weight integration unit 129 sums the weight values to generate a transaction risk index.

Then explain each risk assessment unit in order to explain in detail how each risk assessment unit judges the beneficiary geographic information, beneficiary industry information, user business information, standard condition information, and user transfer channel information in Easy Message. First, the regional risk assessment unit 120 will be explained. Please refer to the first and second figures. The regional risk assessment unit 120 has a regional risk weight table. As shown in the second figure, the regional risk weight table includes plural risk regional information and corresponding to each The area weight value of the risk area information, the area risk assessment unit 120 receives the payee area information in the transaction message, so that the payee area information generates the area weight value corresponding to the area risk weight table. In this embodiment, the risk geographic information is the name of the region, such as North Korea, Iran, Afghanistan, etc. Each region has a different regional risk weight. The weight value can be set according to the economic sanction target regulations of the US Overseas Assets Control Office , Countries or regions that provide funds or support terrorism, or regulations that are targets of United Nations sanctions, determine whether the region is a country that is prone to fraud or money laundering risks. For North Korea, North Korea has all the above sanctions Therefore, if the user places the account of the transaction in North Korea when operating the transaction, the risk of fraud or money laundering will increase relatively, and of course the higher the geographical weight value will be given. Next, for Australia, Australia is not included in the aforementioned sanctions targets. Therefore, Australia is a low-risk region and the lower the geographical weight value it holds.

Next, please refer to the first figure in conjunction with the third figure to illustrate the industry risk assessment unit 122. The industry risk assessment unit 122 has an industry risk weight table, including plural risk industry information and industry weight values corresponding to each risk industry information. The industry risk assessment unit 122 receives the payee industry information in the transaction information to enable the payee industry The information generates industry weight values corresponding to the industry risk weight table. In detail, the industry risk assessment unit 122 judges whether there is a risk of fraud or money laundering according to the industry of the payee user. In this embodiment, when the payee’s profession is generally determined as a soldier, there may be a risk of fraud or money laundering. Relatively lower, the industry weight value is relatively low. However, if the recipient is a trust and investment company, the risk of fraud or money laundering is relatively high, so the industry weight value is relatively high.

Next, please refer to the first figure in conjunction with the fourth figure to illustrate the business risk assessment unit 124. The business risk assessment unit 124 contains a business risk weight table, which includes plural risk business information and a business weight value corresponding to each risk business information. The business risk assessment unit 124 receives the user business information in the transaction message so that the user business information is based on the business The risk weight table generates corresponding business weight values. The transaction abnormality evaluation system 1 can judge whether there is a risk of fraud or money laundering according to the business operated by the user. As shown in the fourth figure, when the user uses "deposit, receive or withdraw cash" and "quickly transfer funds to other accounts" For these business functions, it is generally considered that funds transfer may be fraudulent or money laundered, and involve the procedures of fraud or money laundering, so the set business weight value will be higher. However, if the user's business is "allowing rapid termination of the contract or early termination of the contract after signing the contract", the business does not involve fund transfer, so the risk of fraud or money laundering is considered relatively low, and the set business weight value is just Will be relatively low.

Next, please refer to the first figure in conjunction with the fifth figure to illustrate the standardized risk assessment unit 126. The normative risk assessment unit 126 contains a normative risk weight table, which includes plural risk norm information and normative weight values corresponding to each risk norm information. The normative risk assessment unit 126 receives normative condition information in the transaction message, so that the normative condition information conforms to the norm. The risk weight table corresponds to the standard weight value. The plural risk regulation information belongs to the regulation established by the financial institution. If the financial institution operated by the user “has an independent unit responsible for preventing money laundering and combating capital terrorism, and the board of directors assigns a dedicated supervisor to coordinate and supervise the prevention of money laundering And the implementation of anti-capital terrorism" regulations have more protection for users. Or, the regulations formulated by financial institutions include “properly implement the confirmation of customer identity, conduct customer review and identify the substantive beneficiaries, and regularly review and confirm the validity of overseas company registrations, formulate operating procedures for confirming customer identity, and follow these procedures In detail, the customer due diligence control mechanism and process are detailed, and a computer information system is used to perform Know your customer (KYC) review", which means that the financial institution will confirm the user’s identity and information in detail when remittance. For users A certain understanding of the background of the identity of the user can relatively reduce the risk of users being fraudulent or money laundering fund transfer. Therefore, if these financial institutions have more relevant regulations to protect users, of course, the risk of users being defrauded or money laundering will be relatively reduced. Therefore, the regulation weight value provided by the regulation risk assessment unit 126 is expressed as a negative number.

Next, please refer to the first figure in conjunction with the sixth figure to illustrate the transaction channel risk assessment unit 128. The transaction channel risk assessment unit 128 stores a transaction channel risk weight table, which includes plural risk transaction channel information and a transaction channel weight value corresponding to each risk transaction channel information. The transaction channel risk assessment unit 128 receives the user transfer channel information in the transaction message , And make the user transfer channel information correspondingly generate the transaction channel weight value according to the transaction channel risk weight table. In detail, risk trading channel information is the channel used by users to conduct transactions. Generally speaking, if the user’s trading channel uses counter-counter transactions, the transaction channel can conduct financial transactions face-to-face with the financial institution staff, and the staff can notice the user’s Look or attitude, etc., to determine whether the user has suffered fraud or money laundering, so that the clerk can properly prevent the user from making financial transactions, so the risk of the user being defrauded or money laundering is relatively reduced. However, if the user chooses non-face-to-face transactions, such as Automated Teller Machine (ATM), or through online banking, there is no financial institution staff to assist in identifying the user’s look. When the user may be scammed or When there is money laundering, it is more difficult for someone to come forward to stop it, so that the risk of being defrauded or money laundering is increased, so the weight value of the transaction channel given is relatively increased.

The regional weight value, industry weight value, business weight value, and standard weight value generated by the above-mentioned regional risk assessment unit 120, industry risk assessment unit 122, business risk assessment unit 124, normative risk assessment unit 126, and transaction pipeline risk assessment unit 128 The weight value of the trading channel and the trading channel are integrated into the weight integration unit 129 to generate a trading risk index, and then the abnormal evaluation and analysis device 12 transmits the trading risk index to the display device 14 so that the display device 14 jumps out of the trading risk index to remind management The staff should pay attention to whether the transaction is risky, and the administrator of the financial machine should pay attention to the user’s transaction, or when the transaction risk index is in a high-risk situation, the system can also provide the system to actively reject the user’s transaction to improve user transactions Security.

In this embodiment, if the total transaction risk index of the aforementioned geographical weight value, industry weight value, business weight value, standard weight value, and transaction channel weight value is between 15 and 20, it can be defined as being defrauded or money laundered. If the transaction risk index is between 14 and 7, it can be defined as medium risk. If the transaction risk index is between 0 and 5, it can be defined as low risk. However, the foregoing transaction risk index range is only used as an example for illustration, and the risk level of the transaction risk index is not limited to the foregoing numerical range.

To sum up, this creation adopts artificial intelligence analysis, even if the user uses automatic machinery and equipment for transactions, this creation can automatically analyze the possible fraud or money laundering of the transaction, and can monitor the transaction situation in real time and improve transaction security , At the same time, it can reduce manpower to investigate bad transaction behaviors, save work time and improve anti-fraud and anti-money laundering efficiency.

Only the above are only preferred embodiments of this creation, and are not used to limit the scope of implementation of this creation. Therefore, all equivalent changes or modifications made in accordance with the characteristics and spirit of the application scope of this creation shall be included in the scope of patent application of this creation.

1: Transaction anomaly evaluation system 10: Data input device 12: Abnormal evaluation and analysis device 120: Regional Risk Assessment Unit 122: Industry Risk Assessment Unit 124: Business Risk Assessment Unit 126: Standardize risk assessment unit 128: Transaction Pipeline Risk Assessment Unit 129: Weight Integration Unit 14: display device

The first block diagram of the system created by this book. The second figure is a schematic diagram of the geographical risk weight table created by this book. The third chart is a schematic diagram of the industry risk weight table created by this book. The fourth chart is a schematic diagram of the business risk weight table created by this book. Figure 5 is a schematic diagram of the standardized risk weight table created by this book. The sixth chart is a schematic diagram of the trading channel risk weight table created by this book.

1: Transaction anomaly evaluation system

10: Data input device

12: Abnormal evaluation and analysis device

120: Regional Risk Assessment Unit

122: Industry Risk Assessment Unit

124: Business Risk Assessment Unit

126: Standardize risk assessment unit

128: Transaction Pipeline Risk Assessment Unit

129: Weight Integration Unit

14: display device

Claims (8)

A transaction abnormality evaluation system, including: A data input device that provides input transaction information; An abnormality evaluation and analysis device connected to the data input device, the abnormality evaluation and analysis device contains a risk assessment condition, the abnormality assessment and analysis device receives the transaction message, judges the transaction message according to the risk assessment condition, and generates a transaction risk index; and A display device is connected to the abnormality evaluation and analysis device to receive and display the transaction risk index. The transaction abnormality evaluation system according to claim 1, wherein the risk evaluation condition includes a plurality of risk weight tables, and the abnormality evaluation analysis device includes a weight integration unit to generate the transaction risk index according to the risk weight tables. For example, the transaction abnormality evaluation system described in claim 2, wherein the transaction information includes a beneficiary region information, a beneficiary industry information, a user business information, a standard condition information and a user transfer channel information, and the risk weights The table includes a regional risk weight table, an industry risk weight table, a business risk weight table, a standard risk weight table, and a transaction channel risk weight table. The transaction abnormality evaluation system according to claim 3, wherein the abnormality evaluation and analysis device includes: A regional risk assessment unit, which contains the regional risk weight table, which includes plural risk region information and a regional weight value corresponding to each risk region information. The regional risk assessment unit receives the payment-receiving region information according to the region The risk weight table is evaluated, and the region information of the payment is corresponding to the region weight value; An industry risk assessment unit, which contains a risk weight table for the industry, which includes plural risk industry information and industry weight values corresponding to each risk industry information. The industry risk assessment unit receives the payee’s industry information and bases it on the The industry risk weight table evaluates the industry information of the payee, and correspondingly generates the industry weight value; A business risk assessment unit, which contains a business risk weight table, which includes plural risk business information and a business weight value corresponding to each risk business information. The business risk assessment unit receives the user’s business information and bases it on the business risk The weight table evaluates the user's business information, and correspondingly generates the business weight value; A normative risk assessment unit, which contains the normative risk weight table, which includes plural risk norm information and norm weight values corresponding to each of the risk norm information. The normative risk assessment unit receives the normative condition information to make risk based on the norm The weight table evaluates the criterion condition information, and correspondingly generates the criterion weight value; and A transaction channel risk assessment unit containing a transaction channel risk weight table, which includes plural risk transaction channel information and a transaction channel weight value corresponding to each risk transaction channel information, and the transaction channel risk assessment unit receives the user transfer channel Information, and evaluate the correspondence of the user’s transfer channel information according to the transaction channel risk weight table to generate the transaction channel weight value. The transaction abnormality assessment system according to claim 4, wherein the weight integration unit is connected to the regional risk assessment unit, the business risk assessment unit, the normative risk assessment unit, and the transaction pipeline risk assessment unit to receive and add up the region The weight value, the weight value of the industry, the weight value of the business, the weight value of the specification, and the weight value of the transaction channel generate the transaction risk index. The transaction abnormality evaluation system according to claim 1, wherein the data input device is a keyboard or a signal port. The transaction abnormality evaluation system according to claim 1, wherein the display device is a screen. The transaction abnormality evaluation system according to claim 1, wherein the abnormality analysis and evaluation device is a computer.

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